Parametric Models in Spatial Econometrics: A Survey

Diana A. Mendes () and Vivaldo M. Mendes ()
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Diana A. Mendes: ISCTE-IUL and BRU-IUL
Vivaldo M. Mendes: ISCTE-IUL and BRU-IUL

A chapter in Complexity and Geographical Economics, 2015, pp 51-71 from Springer

Abstract: Abstract The main purpose of this chapter is to review the parametric spatial econometric models that can be applied to regional economics. Spatial econometric methods are based on regression analysis applied to cases where spatial interactions and spatial structures are fundamental characteristics of the process under discussion. The review presented here outlines the basic terminology, the spatial data dependence, the specification of spatial effects, and some basic spatial regression models, i.e., the spatial autoregressive (SAR) model (or spatial lag model), the spatial error model (SEM), the spatial Durbin model (SDM) and the general spatial models—SAC and SARMA. The maximum likelihood estimation for SAR and SEM models it is also presented with some detail.In the context of the European Union, we should emphasize several empirical works in the particular areas of urban economics, economic growth and productivity, and studies dealing with agglomeration and externalities (spillovers). We provide a brief survey of some of the results obtained in these particular areas.

Keywords: Spatial Autocorrelation; Spatial Dependence; Spatial Weight Matrix; Spatial Error Model; Spatial Econometric (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-319-12805-4_3

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